Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation

Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation

Transplant Immunology 32 (2015) 18–22 Contents lists available at ScienceDirect Transplant Immunology journal homepage:

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Transplant Immunology 32 (2015) 18–22

Contents lists available at ScienceDirect

Transplant Immunology journal homepage:

Soluble CD30 does not predict late acute rejection or safe tapering of immunosuppression in renal transplantation Lars L.F.G. Valke a,b,1, Bram van Cranenbroek a,1, Luuk B. Hilbrands b,2,3, Irma Joosten a,⁎,2,3 a b

Department of Laboratory Medicine, Laboratory of Medical Immunology, Radboud University Medical Centre, PO Box 9101 6500HB Nijmegen, the Netherlands Department of Nephrology, Radboud University Medical Centre, PO Box 9101 6500HB Nijmegen, the Netherlands

a r t i c l e

i n f o

Article history: Received 15 August 2014 Received in revised form 27 October 2014 Accepted 28 October 2014 Available online 6 November 2014 Keywords: Acute rejection Renal transplantation Rituximab sCD30

a b s t r a c t Background: Previous reports revealed the potential value of the soluble CD30 level (sCD30) as biomarker for the risk of acute rejection and graft failure after renal transplantation, here we examined its use for the prediction of safe tapering of calcineurin inhibitors as well as late acute rejection. Methods: In a cohort of renal transplant patients receiving triple immunosuppressive therapy we examined whether sCD30 can be used as a marker for safe (rejection-free) discontinuation of tacrolimus at six months after transplantation (TDS cohort: 24 rejectors and 44 non-rejecting controls). Also, in a second cohort of patients (n = 22, rejectors n = 11 and non-rejectors n = 11), participating in a clinical trial of rituximab as induction therapy after renal transplantation (RITS cohort), we examined whether sCD30 could predict the occurrence of late (N3 months post-transplant) acute rejection episodes. sCD30 was measured by ELISA in serum taken before and at several time points after transplantation. Results: Overall, in the TDS cohort sCD30 decreased after transplantation. No difference in sCD30 was observed between rejectors and non-rejecting controls at any of the time points measured. In addition, in the RITS cohort, sCD30 measured at three months after transplantation were not indicative for the occurrence of late acute rejection. Conclusion: In two prospectively followed cohorts of renal transplant patients we found no association between sCD30 and the occurrence of either late acute rejection or acute rejection after reduction of immunosuppression. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Kidney transplantation is the only cure for end-stage renal failure. With the advent of current immunosuppressive therapy both shortterm and long-term graft survival have greatly improved, although chronic deterioration of graft function remains a major clinical problem. A major drawback of this type of therapy is that the drugs are non-specific and have serious side effects, like a greater risk of infection, increased susceptibility to malignancies and faster development of cardiovascular disease [1,2]. Moreover, calcineurin inhibitors, like

Abbreviations: Aza, Azathioprine; AUC, Area under curve; HD, Haemodialysis; MMF, Mycophenolate mofetil; PD, Peritoneal dialysis; PRA, Panel reactive antibody; ROC, Receiver operating characteristic; RITS, Rituximab Induction Therapy Study; sCD30, Soluble CD30; TDS, Tacrolimus Discontinuation Study. ⁎ Corresponding author at: Department of Laboratory Medicine, Laboratory Medical Immunology, Radboud University Medical Centre, PO Box 9101, 6500 HB Nijmegen, The Netherlands. Tel.: +31 243615335; fax: +31 243619415. E-mail addresses: [email protected] (L.L.F.G. Valke), [email protected] (B. van Cranenbroek), [email protected] (L.B. Hilbrands), [email protected] (I. Joosten). 1 Performed the research, analysed the data and wrote the paper. 2 These authors contributed equally to this article. 3 Designed the research, analysed data and wrote the paper. 0966-3274/© 2014 Elsevier B.V. All rights reserved.

tacrolimus, are also nephrotoxic and this feature may contribute to long-term graft loss [2,3]. Therefore, an important goal is to safely reduce the use of immunosuppressive drugs; i.e. lowering the number of drugs or their dose without increasing the risk of rejection. The main problem of this approach is that as yet there are no validated biomarkers to predict safe tapering. Recently, the concentration of soluble CD30 (sCD30) was suggested by Susal et al. as a reliable biomarker for the prediction of kidney graft outcome [4]. Other groups found a similar association between high sCD30 levels and graft loss [5–9]. But as regards the prediction of acute rejection, the data are conflicting [10–12]. The CD30 molecule was originally identified on the surface of ReedSternberg cells in Hodgkin lymphoma. It is a member of the tumour necrosis factor/nerve growth factor super family and is a relatively large glycoprotein of 120 kDa [13]. CD30 is not expressed on resting immune cells but on diverse activated cells like T- and B-lymphocytes, and dendritic cells. (14) Recent studies have shown that CD30 has an important role in the generation of memory T-cell responses and the regulation of the balance between Th1-/Th2-responses, as it acts as a co-stimulatory molecule [14]. Another important finding is that even under cyclosporine treatment, CD30+ lymphocytes can still be induced by alloantigens. The absolute number of CD30+ cells is decreased by cyclosporine, but T cell activation still occurs [15]. Therefore it can be envisaged that

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CD30+ cells have a role in graft rejection even under immunosuppressive treatment. Upon activation of T cells, CD30 can be released as a soluble molecule in the bloodstream. Due to its size, sCD30 is not filtrated by the kidney and its concentration is not influenced by renal failure, although the route of metabolization of sCD30 is still unknown. Here, we investigated if sCD30 could predict the occurrence of acute rejection in renal transplantation patients in whom immunosuppression was reduced. In the same patient cohort, we previously showed that the ratio between memory T cells and Tregs, and the changes in distribution of naïve, effector and memory T cells enabled to identify patients in whom immunosuppression could safely be reduced at six months after transplantation [16]. In the current study, we furthermore examined in another patient cohort whether sCD30 could predict late acute rejection episodes (beyond 3 months after transplantation) using a case-control design. To our knowledge, this is the first study addressing the role of sCD30 in the prediction of acute rejection after tapering of immunosuppression and late acute rejection. 2. Materials and methods


Table 1 Tacrolimus Discontinuation Study (TDS) patient characteristics. Parameter




Number of patients Female (%) Patient age (years, mean ± SD) Donor age (years, mean ± SD) Cold ischemic time (hours, mean ± SD) Retransplantation (%) Living donor (%) HLA A/B/DR mismatches (mean ± SD) PRA N5% (%) Dialysis before transplantation None (%) HD (%) PD (%) HD and PD sequentially (%) eGFR six months post transplantation (ml/min/1.73 m2; median, (range)) eGFR ten months post transplantation (ml/min/1.73 m2; median, (range))

24 8 (33%) 45.4 ± 15.5 49.4 ± 13.5 11.0 ± 9.74 0 (0%) 12 (50%) 2.3 ± 0.8 3 (13%)

44 16 (36%) 41.6 ± 14.2 47.0 ± 12.4 12.0 ± 8.81 7 (16%) 18 (41%) 1.9 ± 1.2 15 (34%)

1.00 0.804 0.595 0.637 0.004 0.610 0.095 0.083

2 (8%) 15 (63%) 7 (29%) 0 (%) 70 (38–126)

6 (14%) 22 (50%) 11 (25%) 5 (11%) 76.0 (37–147)

0.703 0.445 0.771 0.153 0.741

65 (26–125)

81 (42–145)


HLA, human leukocyte antigen; PRA, panel reactive antibody; PD, peritoneal dialysis; HD, haemodialysis; eGFR, estimated glomular filtration rate (calculated with MDRD4formula).

2.1. Patient cohorts and immunosuppressive treatment 2.1.1. Tacrolimus Discontinuation Study (TDS) The patients included in this study received a renal allograft at the Radboud university medical center between January 2000 and December 2004. Standard triple immunosuppressive therapy consisted of tacrolimus in combination with mycophenolate mofetil and prednisolone. Patients received 100 mg of prednisolone intravenously during the first 3 days after transplantation and subsequently an oral dose of 15– 25 mg/day (depending on body weight), which was tapered to a maintenance dose of 0.1 mg/kg/day. Tacrolimus was started at day 1 or 2 after transplantation at 0.15 mg/kg/day (administered twice daily orally) and the dose was subsequently adjusted to achieve target whole-blood concentrations of 15–20 ng/milliliter during days 0–14, 10–15 ng/milliliter during weeks 3–6, and 5–10 ng/milliliter from week 7 onwards. Mycophenolate mofetil (MMF) was administered at 1000 mg twice daily with a dose reduction to 750 mg twice daily at 2 weeks after transplantation, unless the patient weighed more than 90 kg. Induction therapy with polyclonal or monoclonal antibodies was not used. At 4 months after transplantation, immunological low risk patients were selected for reduction of their immunosuppression (including withdrawal of tacrolimus to prevent long term nephrotoxicity). They had to meet the following inclusion criteria: stable graft function, at least 1 HLA-B and 1 HLA-DR match between donor and recipient, panel reactive antibodies (PRA) ≤ 85% before transplantation, and Caucasian race. Patients who received a kidney from a HLA-identical living donor, patients with two or more previously failed grafts, and patients who had experienced a steroid-resistant acute rejection episode after their current transplantation were excluded for immunological reasons. In addition, patients with severe osteoporosis and patients with bone marrow suppression were excluded because they received an alternative treatment regimen. First, MMF was substituted for azathioprine (Aza, 3 mg/kilogram daily). The dose of Aza was adjusted in case of leukocytopenia or elevated liver enzymes. In case patients did not tolerate a minimum Aza dose of 2 mg/kilogram/day, MMF was reintroduced (750 mg twice daily). Two months later, at six months after transplantation, the tacrolimus dose was gradually reduced to zero over a period of 4 weeks. Meanwhile, the prednisolone dose was increased to 0.15 mg/kilogram/day. The resulting maintenance immunosuppressive therapy after conversion consisted of azathioprine (at least 2 mg/kilogram/day; otherwise MMF 750 mg twice daily) and prednisolone (0.15 mg/kilogram/day). Patients were evaluated for acute rejection episodes during the first 6 months after withdrawal of tacrolimus. All acute rejection episodes were histological confirmed.

2.1.2. Rituximab Induction Therapy Study (RITS) Patients included in this cohort participated in a randomized clinical trial assessing the efficacy and safety of rituximab induction therapy when added to standard triple immunosuppressive therapy in renal transplantation. Participants received a renal allograft in the Radboud university medical center between December 2007 and June 2012. Inclusion criteria were: Age above 18 years and for female patients the absence of pregnancy and willingness not to become pregnant within 12 months after transplantation. Patients with haemolytic uremic syndrome as original disease, recurrence of focal segmental glomerosclerosis in a previous graft, more than two previously failed

Fig. 1. Scatter plot of soluble CD30 concentration pre transplantation, at 4 months after transplantation (inclusion of study), and pre tapering of immunosuppression (6 months after transplantation) in the Tacrolimus Discontinuation Study cohort. Every dot represents the result from a single patient, the median is given.


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Fig. 2. Difference in sCD30 concentration between rejectors and non-rejectors in the Tacrolimus Discontinuation Study cohort a) pre transplantation; b) at 4 months after transplantation (inclusion of study), and c) pre tapering of tacrolimus (6 months after transplantation); every dot represents the result from a single patient, the median is given.

grafts and/or PRA N85%, previous treatment with anti-CD20 antibodies, total white blood cell count b3,000/mm3, platelet count b75,000/mm3, active infection with hepatitis B, C or HIV, history of tuberculosis, and those who received a kidney form an HLA-identical living donor were excluded. Patients were randomized to rituximab (MabThera®) 375 mg/m2 or placebo intravenously on day zero. Patients and physicicans were blinded for treatment. The dosages of steroids, tacrolimus and MMF were similar as described above for the TDS cohort. Patients with a late acute rejection were defined as patients who had an acute rejection episode beyond 3 months after transplantation, with no previous rejection episode. They were matched with a non-rejector for treatment, gender, age, and immunological risk stratification (PRA ≤ 5% or N5% and first or second transplant). IRB approval was obtained for both studies and all patients gave written informed consent. 2.2. Sample collection 2.2.1. TDS Serum samples were collected before transplantation, at 4 months after transplantation, and prior to the start of tacrolimus reduction (6 months after transplantation). After collection, samples were stored at −20 °C until further use. For the current analysis, the samples of 24 patients with an acute rejection and of 44 patients without an acute rejection after tacrolimus discontinuation were available. 2.2.2. RITS Serum samples were collected (and stored at − 20 °C) at three months after transplantation. For this analysis, sera were available of 11 patients with a late acute rejection and of 11 matched non-rejectors. 2.3. Measurement of sCD30 The measurement of soluble CD30 test was performed with a commercially available ELISA (eBioscience, Vienna, Austria) according to the manufacturer's instructions. On a number of samples we performed analysis of sCD30 in parallel, using both the “Instant Kit” and the “Antibody Pair Kit”. We found an excellent correlation (n = 42, r = 0.94; p = b0.00001), and for practical reasons, chose to use the Antibody Pair Kit for final analysis. All measurements were performed by a single researcher who was blinded for the rejection status of the patients.

Although the samples were stored for a longer period of time, measurements are considered robust, as e.g. repeated freeze-thaw-cycles were shown not to have an effect on soluble CD30 concentrations [17].

2.4. Statistical analysis Statistical analysis was performed with Prism GraphPad 5.0 (GraphPad Software, La Jolla, CA, USA) using paired and unpaired Student's t-tests in case of Gaussian distribution (tested with ShapiroWilk W-test) and Mann-Whitney U-test in case of non-Gaussian distribution. Receiver operating curves were formed and associated area under the curve calculated to determine the predictive capacity of the biomarkers. A p b 0.05 was considered as statistically significant. 3. Results 3.1. sCD30 in the TDS cohort In the TDS cohort, the samples of 24 patients with an acute rejection and of 44 patients without acute rejection were available for the current analysis. The characteristics of these patients are given in Table 1. To gain more overall insight in the course of sCD30 levels over time, we included three time points: 1) before transplantation, 2) at 4 months after transplantation and 3) just before reduction of tacrolimus at six months after transplantation. In these patients, the sCD30 concentration had a median value of 126.8 (range 0.0– 338.0) ng/milliliter before transplantation with a decrease to a median value of 53.0 (range 13.6–222.6) ng/milliliter (p b 0.0001) at four months post-transplant, and remaining at that level until 6 months post-transplantation (median value just before tacrolimus tapering; 53.2 (range 7.3–331.6) ng/milliliter) (Fig. 1). In patients with an acute rejection after discontinuation of tacrolimus, this occurred at a median of 53 days (range 14– 143 days) after the start of tapering tacrolimus. When comparing sCD30 concentrations between rejectors and non-rejectors, as shown in Fig. 2, there was no significant difference between the two groups, either prior to transplantation (rejectors had a median value of 122.0 (range 0–307.9) ng/milliliter versus median 128.2 (range 51.6–338.0) ng/milliliter in non-rejectors; NS), at 4 months after transplantation (median 47.6 (range 13.6– 222.6) ng/milliliter versus median 55.3 (range 23.8–153.5) ng/milliliter; NS) or pre withdrawal of tacrolimus (median 53.4 (range 19.4–135.2) ng/milliliter versus median 52.8 (range 7.4–331.0) ng/milliliter; NS). To determine whether sCD30 has any predictive value at any of the three different time points measured; we calculated the area under the curve (AUC) of the ROC-curve. AUC values for the curves obtained pretransplantation, at 4 months after transplantation, and just before tapering of tacrolimus were 0.52, 0.58 and 0.51, respectively, indicating the lack of predictive value at all tested time points. Also, the sCD30 concentration at 6 months after transplantation did not correlate with time until rejection (r = 0.19, p = 0.42, data not shown). There was no significant difference in eGFR between patients with high (N40 ng/milliliter) and low (b40 ng/milliliter) sCD30 concentration (measured at six months after transplantation and four months after tapering of tacrolimus, respectively) neither before nor after withdrawal of tacrolimus (data not shown).

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3.2. sCD30 in the RITS cohort Samples of 11 patients with late acute rejection were compared with those of 11 matched non-rejectors in the RITS cohort; patient demographics are given in Table 2. Serum sCD30 levels measured at three months post-transplant did not significantly differ between rejectors and non-rejectors (median 35.1 (range 13.2–270.9) ng/milliliter versus median 27.4 (range 6.5–62.8) ng/milliliter; p = 0.15; Fig. 3). Accordingly, sCD30 had no predictive value for the occurrence of late acute rejection (ROC curve AUC = 0.69; p = 0.14). The median time interval between blood sampling and diagnosis of rejection was 55 days (range 8–112 days) and sCD30 concentration in rejectors did not correlate with time until acute rejection (r = 0.56, p = 0.07, data not shown). We also compared sCD30 levels in rituximab versus placebo treated patients (rejectors plus non-rejectors), but did not find a difference (p = 0.57; data not shown).

4. Discussion Here, we investigated the predictive value of serum soluble CD30 levels for 1) rejection after tapering of immunosuppression and 2) late acute rejection. We found no indication that serum sCD30 can be of use as biomarker in these specific situations. In previous reports, the post-transplant sCD30 concentration was reported as a promising predictor of kidney graft outcome [4–8]. While most reports focus upon the correlation between high post transplant sCD30 concentration and graft loss, only limited evidence is available for the prediction of acute rejection. Besides the conflicting results, reports use different time points on which sCD30 is determined which can influence outcome as sCD30 levels decrease dramatically in the post transplant period. In patients included in our tacrolimus discontinuation study cohort sCD30 levels could not predict acute rejection after tapering of tacrolimus from 6 months after transplantation. This was true for pre-transplantation as well as for pre-tapering (6 months after transplantation) sCD30 concentration. Previously, high pre-transplantation sCD30 levels were associated with acute rejection [17–19], although this could not be confirmed in other studies [10–12,20,21]. In addition, a recent meta-analysis showed that pre transplant sCD30 concentrations have a low predictive value for acute rejection after renal transplantation with an AUC of a summary ROC curve of only 0.60 [9]. The authors recommended to perform additional prospective studies to assess the predictive value of sCD30 concentrations. The serum samples that were used for our analysis were collected as part of a prospective cohort study and a prospective clinical trial, respectively. A disadvantage of sCD30 as marker for allograft rejection is that it is a nonspecific immune marker that can fluctuate over time, depending on different factors, e.g. infectious status.[22]. In our study this was exemplified by a non-rejector with a very high sCD30 concentration (330 ng/milliliter) and who turned out to have an abscess after extraction of a wisdom tooth. Also, CMV disease has been reported to result in Table 2 Rituximab Induction Therapy Study (RITS) patient characteristics. Parameter




Number of patients (%) Rituximab treatment (%) Female (%) Patient age (years, mean ± SD) Donor age (years, mean ± SD) Cold ischemic time (hours, mean ± SD) Retransplantation (%) Living donor (%) HLA A/B/DR mismatches (mean ± SD) PRA N5% (%) Dialysis None (%) HD (%) PD (%) HD and PD sequentially (%)

11 (50%) 6 (54%) 3 (27%) 50.0 ± 12.2 50.1 ± 7.8 7.42 ± 9.05 0 (0%) 7 (64%) 3.5 ± 1.6 1 (9%)

11 (50%) 6 (54%) 3 (27%) 50.5 ± 11.2 50.6 ± 13.0 7.09 ± 7.20 0 (0%) 7 (64%) 3.0 ± 1.3 1 (9%)

1.00 1.00 0.928 0.922 0.906 1.00 1.00 0.392 1.00

1 (9%) 3 (27%) 2 (18%) 5 (45%)

4 (36%) 3 (27%) 3 (27%) 1 (9%)

0.311 1.00 1.00 0.149

HLA, human leukocyte antigen; PRA, panel reactive antibody; PD, peritoneal dialysis; HD, haemodialysis.

Fig. 3. Difference in sCD30 concentration between rejectors and non-rejectors in Rituximab Induction Therapy Study cohort; every dot represents the result from a single patient, the median is given.

a transient rise in sCD30 levels [23]. This indicates that sole measurements of sCD30 have limited value. Also, the influence of different immunosuppressive drugs on sCD30 levels is not clear. Higher whole blood concentrations of tacrolimus were correlated with higher sCD30 concentrations, while MMF and prednisone did not have a clear influence on sCD30 [24]. The role of sCD30 in the prediction of (acute) rejection has also been investigated in non-kidney transplantation. So far, the predictive value of sCD30 is unclear with conflicting evidence in liver [25,26], lung, [27, 28], and heart transplantation [29]. In summary, our study did not indicate a role for serum sCD30 levels in the prediction of acute rejection. The main limitation of our study is the small number of patients. Therefore possible differences between groups of patients may be missed. On the other hand, a robust biomarker should yield significant outcomes also in smaller patient cohorts, especially when they are relatively homogeneous as was the case in our study. There is a clear need for concerted, multi-centre actions to establish reliable and robust biomarkers. Funding sources LV received a research grant from the Radboud Honours Programme Medical Sciences from the Radboud University Nijmegen, the Netherlands. References [1] Andres A. Cancer incidence after immunosuppressive treatment following kidney transplantation. Crit Rev Oncol Hematol 2005;56:71–85. [2] Taylor AL, Watson CJ, Bradley JA. Immunosuppressive agents in solid organ transplantation: Mechanisms of action and therapeutic efficacy. Crit Rev Oncol Hematol 2005;56:23–46. [3] Halloran PF. Immunosuppressive drugs for kidney transplantation. N Engl J Med 2004;351:2715–29. [4] Susal C, Dohler B, Sadeghi M, Salmela KT, Weimer R, Zeier M, et al. Posttransplant sCD30 as a Predictor of Kidney Graft Outcome. Transplantation 2011;91:1364–9. [5] Pelzl S, Opelz G, Daniel V, Wiesel M, Susal C. Evaluation of posttransplantation soluble CD30 for diagnosis of acute renal allograft rejection. Transplantation 2003;75: 421–3. [6] Susal C, Pelzl S, Simon T, Opelz G. Advances in pre- and posttransplant immunologic testing in kidney transplantation. Transplant Proc 2004;36:29–34. [7] Dong W, Shunliang Y, Weizhen W, Qinghua W, Zhangxin Z, Jianming T, et al. Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30. Transpl Immunol 2006;16:41–5. [8] Delgado JC, Pavlov IY, Shihab FS. Post-transplant increased levels of serum sCD30 is a marker for prediction of kidney allograft loss in a 5-year prospective study. Transpl Immunol 2009;22:1–4. [9] Chen Y, Tai Q, Hong S, Kong Y, Shang Y, Liang W, et al. Pretransplantation soluble CD30 level as a predictor of acute rejection in kidney transplantation: a metaanalysis. Transplantation 2012;94:911–8.


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